Instructions to use fusing/ddpm-cifar10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fusing/ddpm-cifar10 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fusing/ddpm-cifar10", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "DDPMPipeline", | |
| "_module": "modeling_ddpm.py", | |
| "scheduler": [ | |
| "diffusers", | |
| "DDPMScheduler" | |
| ], | |
| "unet": [ | |
| "diffusers", | |
| "UNetUnconditionalModel" | |
| ] | |
| } | |